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https://github.com/danswer-ai/danswer.git
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463340b8a1
* remove title for slack * initial working code * simplification * improvements * name change to information_content_model * avoid boost_score > 1.0 * nit * EL comments and improvements Improvements: - proper import of information content model from cache or HF - warm up for information content model Other: - EL PR review comments * nit * requirements version update * fixed docker file * new home for model_server configs * default off * small updates * YS comments - pt 1 * renaming to chunk_boost & chunk table def * saving and deleting chunk stats in new table * saving and updating chunk stats * improved dict score update * create columns for individual boost factors * RK comments * Update migration * manual import reordering
121 lines
4.2 KiB
Python
121 lines
4.2 KiB
Python
import os
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import shutil
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from collections.abc import AsyncGenerator
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from contextlib import asynccontextmanager
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from pathlib import Path
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import sentry_sdk
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import torch
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import uvicorn
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from fastapi import FastAPI
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from sentry_sdk.integrations.fastapi import FastApiIntegration
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from sentry_sdk.integrations.starlette import StarletteIntegration
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from transformers import logging as transformer_logging # type:ignore
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from model_server.custom_models import router as custom_models_router
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from model_server.custom_models import warm_up_information_content_model
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from model_server.custom_models import warm_up_intent_model
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from model_server.encoders import router as encoders_router
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from model_server.management_endpoints import router as management_router
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from model_server.utils import get_gpu_type
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from onyx import __version__
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from onyx.utils.logger import setup_logger
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from shared_configs.configs import INDEXING_ONLY
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from shared_configs.configs import MIN_THREADS_ML_MODELS
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from shared_configs.configs import MODEL_SERVER_ALLOWED_HOST
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from shared_configs.configs import MODEL_SERVER_PORT
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from shared_configs.configs import SENTRY_DSN
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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os.environ["HF_HUB_DISABLE_TELEMETRY"] = "1"
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HF_CACHE_PATH = Path(os.path.expanduser("~")) / ".cache/huggingface"
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TEMP_HF_CACHE_PATH = Path(os.path.expanduser("~")) / ".cache/temp_huggingface"
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transformer_logging.set_verbosity_error()
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logger = setup_logger()
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def _move_files_recursively(source: Path, dest: Path, overwrite: bool = False) -> None:
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"""
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This moves the files from the temp huggingface cache to the huggingface cache
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We have to move each file individually because the directories might
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have the same name but not the same contents and we dont want to remove
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the files in the existing huggingface cache that don't exist in the temp
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huggingface cache.
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"""
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for item in source.iterdir():
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target_path = dest / item.relative_to(source)
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if item.is_dir():
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_move_files_recursively(item, target_path, overwrite)
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else:
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target_path.parent.mkdir(parents=True, exist_ok=True)
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if target_path.exists() and not overwrite:
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continue
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shutil.move(str(item), str(target_path))
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@asynccontextmanager
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async def lifespan(app: FastAPI) -> AsyncGenerator:
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gpu_type = get_gpu_type()
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logger.notice(f"Torch GPU Detection: gpu_type={gpu_type}")
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app.state.gpu_type = gpu_type
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if TEMP_HF_CACHE_PATH.is_dir():
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logger.notice("Moving contents of temp_huggingface to huggingface cache.")
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_move_files_recursively(TEMP_HF_CACHE_PATH, HF_CACHE_PATH)
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shutil.rmtree(TEMP_HF_CACHE_PATH, ignore_errors=True)
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logger.notice("Moved contents of temp_huggingface to huggingface cache.")
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torch.set_num_threads(max(MIN_THREADS_ML_MODELS, torch.get_num_threads()))
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logger.notice(f"Torch Threads: {torch.get_num_threads()}")
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if not INDEXING_ONLY:
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logger.notice(
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"The intent model should run on the model server. The information content model should not run here."
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)
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warm_up_intent_model()
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else:
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logger.notice(
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"The content information model should run on the indexing model server. The intent model should not run here."
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)
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warm_up_information_content_model()
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yield
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def get_model_app() -> FastAPI:
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application = FastAPI(
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title="Onyx Model Server", version=__version__, lifespan=lifespan
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)
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if SENTRY_DSN:
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sentry_sdk.init(
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dsn=SENTRY_DSN,
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integrations=[StarletteIntegration(), FastApiIntegration()],
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traces_sample_rate=0.1,
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)
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logger.info("Sentry initialized")
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else:
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logger.debug("Sentry DSN not provided, skipping Sentry initialization")
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application.include_router(management_router)
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application.include_router(encoders_router)
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application.include_router(custom_models_router)
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return application
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app = get_model_app()
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if __name__ == "__main__":
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logger.notice(
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f"Starting Onyx Model Server on http://{MODEL_SERVER_ALLOWED_HOST}:{str(MODEL_SERVER_PORT)}/"
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)
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logger.notice(f"Model Server Version: {__version__}")
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uvicorn.run(app, host=MODEL_SERVER_ALLOWED_HOST, port=MODEL_SERVER_PORT)
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